Abstract: Driven by the global motivation to achieve zero-emission transportation, the transportation sector has been experiencing rapid revolution of electrification. Unfortunately, the mature technologies used in the present electrification of ground vehicles and ships cannot be directly applied when tackling the distinct set of challenges posed by the operating environment of a hybrid or electric aircraft, which is characterized by high altitude and severe operating conditions as well as the complicated mission profiles. When designing an electric aircraft propulsion system which will be subjected to these harsh circumstances, reliability must heavily influence all decisions. But simultaneously, the drivetrain additionally needs to be lightweight, compact, efficient, and cost effective. These various objectives typically prove to be impossible to satisfy concurrently, and therefore trade-offs need to be established in order to extract the highest overall system performance.
This webinar focuses on AI-based multi-objective design optimization of electric propulsion drive systems for hybrid and electric aircraft. The presented approach employs a genetic algorithm which generates many high performing designs that exhibit optimal trade-offs between competing objectives, such as reliability and specific power. Computationally-efficient time-based electro-thermal simulations of multiple converter topologies, which forms the backbone of the framework, will be discussed. Also, the sizing and selection of all system elements realized though off-the-shelf components will be examined. Finally, a software package has been developed which encapsulates the described framework, and its functionality will be validated with two case studies of propulsion power converter designs.
